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Genetic Fuzzy Rule-Based Modelling of Dynamic Systems Using Time Series

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Swarm and Evolutionary Computation (EC 2012, SIDE 2012)

Abstract

The paper presents a genetic fuzzy rule-based technique for the modelling of generalized time series (containing both, numerical and non-numerical, qualitative data) which are a comprehensive source of information concerning the behaviour of many complex systems and processes. The application of the proposed approach to the fuzzy rule-based modelling of an industrial gas furnace system using measurement data available from the repository at the http://www.stat.wisc.edu/~reinsel/bjr-data (the so-called Box-Jenkins’ benchmark) is also presented.

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References

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© 2012 Springer-Verlag Berlin Heidelberg

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Gorzałczany, M.B., Rudziński, F. (2012). Genetic Fuzzy Rule-Based Modelling of Dynamic Systems Using Time Series. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_27

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  • DOI: https://doi.org/10.1007/978-3-642-29353-5_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29352-8

  • Online ISBN: 978-3-642-29353-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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